ArticleBMC cancer2025
Development and validation of a histological calculator for anastomotic margins to predict anastomotic failure among rectal cancer patients treated with neoadjuvant chemoradiotherapy.
Article in BMC cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
purposeTo identify histological features of anastomotic margins and develop a prediction model for anastomotic failure (AF) in rectal cancer (RC) patients with neoadjuvant chemoradiotherapy (nCRT).
methodsA total of 350 pairs anastomotic "doughnuts" from RC with nCRT were randomly divided into the primary and validation cohorts at a ratio of 7:3. The histological features were identified and constructed using LASSO (Least absolute shrinkage and selection operator) regression to develop the radiation-induced colorectal injury (RCI) score. An AF prediction mode based on the RCI score was built and evaluated using the area under the receiver operating characteristic curve (AUC), decision curve analysis (DCA), and the DeLong test.
resultsThe primary cohort consisted of 245 patients, among whom AF occurred in 26.9% of cases, while the validation cohort comprised 105 patients, with an AF rate of 24.8%. The RCI score of anastomotic margins showed a significant correlation with AF (odds ratio: 2.963; 95% confidence interval [CI]: 2.298-3.822; P < 0.001). Multivariable analysis identified body mass index (BMI) < 18.5, tumor location, long-course radiotherapy, and the RCI score as independent predictors for AF. The nomogram based on the RCI score exhibited good discrimination in both the primary cohort (AUC: 0.886; 95% CI: 0.840-0.931), with a sensitivity of 86.36% (95% CI, 75.7-93.6%) and specificity of 76.54% (95% CI, 69.6-82.5%). Calibration curves revealed satisfactory agreement between the predicted and the observed probabilities.
conclusionsThe comprehensive nomogram incorporating the RCI score could assist physicians in predicting AF and formulating personalized treatment strategies for RC patients with neoadjuvant radiotherapy.
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